Rylan Schaeffer

According to our database, Rylan Schaeffer authored at least 28 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment.

Elyas Obbad, Iddah Mlauzi, Brando Miranda, Rylan Schaeffer, Kamal Obbad, Suhana Bedi, Sanmi Koyejo

CoRR, 2024

Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World.

Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo

CoRR, 2024

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?

Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez

CoRR, 2024

Open Problems in Technical AI Governance.

Anka Reuel, Ben Bucknall, Stephen Casper, Tim Fist, Lisa Soder, Onni Aarne, Lewis Hammond, Lujain Ibrahim, Alan Chan, Peter Wills, Markus Anderljung, Ben Garfinkel, Lennart Heim, Andrew Trask, Gabriel Mukobi, Rylan Schaeffer, Mauricio Baker, Sara Hooker, Irene Solaiman, Alexandra Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel J. Kochenderfer, Robert Trager

CoRR, 2024

Uncovering Latent Memories: Assessing Data Leakage and Memorization Patterns in Large Language Models.

Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R. Fiete

CoRR, 2024

In-Context Learning of Energy Functions.

Rylan Schaeffer, Mikail Khona, Sanmi Koyejo

CoRR, 2024

Quantifying Variance in Evaluation Benchmarks.

Lovish Madaan, Aaditya K. Singh, Rylan Schaeffer, Andrew Poulton, Sanmi Koyejo, Pontus Stenetorp, Sharan Narang, Dieuwke Hupkes

CoRR, 2024

Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations.

Rylan Schaeffer, Victor Lecomte, Dhruv Bhandarkar Pai, Andres Carranza, Berivan Isik, Alyssa Unell, Mikail Khona, Thomas E. Yerxa, Yann LeCun, SueYeon Chung, Andrey Gromov, Ravid Shwartz-Ziv, Sanmi Koyejo

CoRR, 2024

Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?

Rylan Schaeffer, Hailey Schoelkopf, Brando Miranda, Gabriel Mukobi, Varun Madan, Adam Ibrahim, Herbie Bradley, Stella Biderman, Sanmi Koyejo

CoRR, 2024

Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data.

Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey, Rafael Rafailov, Henry Sleight, John Hughes, Tomasz Korbak, Rajashree Agrawal, Dhruv Pai, Andrey Gromov, Daniel A. Roberts, Diyi Yang, David L. Donoho, Sanmi Koyejo

CoRR, 2024

Bridging Associative Memory and Probabilistic Modeling.

Rylan Schaeffer, Nika Zahedi, Mikail Khona, Dhruv Pai, Sang T. Truong, Yilun Du, Mitchell Ostrow, Sarthak Chandra, Andres Carranza, Ila Rani Fiete, Andrey Gromov, Sanmi Koyejo

CoRR, 2024

Investigating Data Contamination for Pre-training Language Models.

Minhao Jiang, Ken Ziyu Liu, Ming Zhong, Rylan Schaeffer, Siru Ouyang, Jiawei Han, Sanmi Koyejo

CoRR, 2024

2023

Incidental Polysemanticity.

Victor Lecomte, Kushal Thaman, Trevor Chow, Rylan Schaeffer, Sanmi Koyejo

CoRR, 2023

Pretraining on the Test Set Is All You Need.

Rylan Schaeffer

CoRR, 2023

Invalid Logic, Equivalent Gains: The Bizarreness of Reasoning in Language Model Prompting.

Rylan Schaeffer, Kateryna Pistunova, Samar Khanna, Sarthak Consul, Sanmi Koyejo

CoRR, 2023

Deceptive Alignment Monitoring.

Andres Carranza, Dhruv Pai, Rylan Schaeffer, Arnuv Tandon, Sanmi Koyejo

CoRR, 2023

FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation.

Dhruv Pai, Andres Carranza, Rylan Schaeffer, Arnuv Tandon, Sanmi Koyejo

CoRR, 2023

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle.

Rylan Schaeffer, Mikail Khona, Zachary Robertson, Akhilan Boopathy, Kateryna Pistunova, Jason W. Rocks, Ila Rani Fiete, Oluwasanmi Koyejo

CoRR, 2023

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models.

Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Are Emergent Abilities of Large Language Models a Mirage?

Rylan Schaeffer, Brando Miranda, Sanmi Koyejo

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells.

Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristóbal Eyzaguirre, Sanmi Koyejo, Ila Fiete

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Emergence of Sparse Representations from Noise.

Trenton Bricken, Rylan Schaeffer, Bruno A. Olshausen, Gabriel Kreiman

Proceedings of the International Conference on Machine Learning, 2023

2022

No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit.

Rylan Schaeffer, Mikail Khona, Ila Fiete

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Streaming Inference for Infinite Feature Models.

Rylan Schaeffer, Yilun Du, Gabrielle K. Liu, Ila Fiete

Proceedings of the International Conference on Machine Learning, 2022

Streaming Inference for Infinite Non-Stationary Clustering.

Rylan Schaeffer, Gabrielle Kaili-May Liu, Yilun Du, Scott Linderman, Ila Rani Fiete

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

An Algorithmic Theory of Metacognition in Minds and Machines.

Rylan Schaeffer

CoRR, 2021

Efficient online inference for nonparametric mixture models.

Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Rani Fiete

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice.

Rylan Schaeffer, Mikail Khona, Leenoy Meshulam, International Brain Laboratory, Ila Fiete

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020